ABSTRACT The goal of this project is to develop, implement, optimize, and validate online methods to predict and monitor cognitive and functional decline in elders with normal cognition (CN), subjective memory complaints (SMC), and mild cognitive impairment (MCI). We will develop online versions of the Clinical Dementia Rating Scale (CDR) and the Financial Capacity Instrument-Short Form (FCI-SF). We will also use the existing Brain Health Registry (BHR) and the Cogstate Brief Battery. Using all information together we will develop composite scores that predict ?-amyloid (A?) positivity and cognitive and functional decline. A major obstacle to providing care and developing new therapeutics is the difficulty identifying those at risk for Alzheimer?s disease (AD) or undergoing cognitive and functional decline. Therefore, the development and validation of scalable, accessible screening tools is a critical unmet need. We will use established cohorts at UCSF, Mayo Clinic, Washington University, and University of Alabama Birmingham, comprised of participants who are already followed longitudinally through uniform data set (UDS) collection and are well-characterized in terms of clinical, cognitive, functional, and A? status. All online instruments will be implemented within the BHR, an online registry with over 52,000 participants and a well-established infrastructure for collecting self- and study-partner- reported data and remote cognitive testing. First, during a one-year Pilot Phase, we will develop, implement, and optimize electronic versions of the CDR and FCI-SF (e-CDR and the e-FCI), first using item response theory and then iteratively optimizing electronic instruments based on usability, user feedback, internal consistency, reliability, convergent/divergent validity, and input from experts. These pilot studies will be performed on 310 CN, SMC, and MCI participants and study partners across 3 sites with existing, longitudinal clinical data. Second, during a 4-year validation phase, we will validate e-instruments by comparing data obtained at home online with data obtained in research clinics in 520 participants and study partners across 4 sites. In addition to the newly-developed eCDR and eFCI, BHR data will include the Cogstate Brief Battery and additional self-report questionnaires. Third, we will determine whether online instruments both measure and predict cognitive and functional decline by following the participants longitudinally for 4 years. Fourth, we will determine the ability of online instruments to predict A? PET positivity. An essential component of these analyses will be the development and validation of new cognitive and functional composite scores, composed of multiple online measures. The results of this project are likely to lead to improved methods for AD screening that can be used in clinical trials. Ultimately these highly scalable online methods may be used in clinical practice and multiple healthcare settings to identify people at risk for and with cognitive and functional decline and AD, leading to prevention of AD and improved healthcare for neurodegenerative disorders.